Wireless communication networks transmit communication signals in the downlink over radio frequency channels from fixed transceivers, known as base stations, to mobile user equipment (UE) within a geographic area normally referred to as a cell. Similarly, the UE can transmit signals in the uplink to one or more of the base stations. In both cases, the received signal may be characterized as the transmitted signal, altered by channel effects, plus noise and interference.
To recover the transmitted signal from a received signal, a receiver must estimate both the channel and the noise/interference. The characterization of a channel is typically referred to as channel state information (CSI). One known way to estimate a channel is to periodically transmit known reference symbols, commonly referred to as pilot symbols. Since the reference symbols are known by the receiver, any deviation in the received symbols from the reference symbols (after the estimated noise/interference is removed) is caused by channel effects. An accurate estimate of CSI allows a receiver to more accurately recover transmitted signals from received signals.
In addition, by transmitting CSI from the receiver to a transmitter, the transmitter can select the transmission characteristics such as coding, modulation, and the like best suited for the current channel state. This is widely known as channel-dependent link adaptation. For example, UEs in a wireless communication network can transmit succinct, direct channel state information to the network without substantially increasing uplink overhead. The UE receives and processes reference symbols over a set of non-uniformly spaced sub-carriers, selected according to a scheme synchronized to the network. In another example, the network computes accurate channel estimates based on infrequently transmitted CSI feedback data from a UE. Both of these techniques typically involve two steps. A time domain tap delay channel model is first constructed from the inverse quantized CSI feedback samples. The time domain tap delay channel model is then frequency-transformed to obtain frequency response estimates of the downlink communication channel. These techniques effectively estimate the CSI between a pair of transmitting and receiving antennas. In a system with multiple input and multiple output (MIMO) antennas, these estimation techniques are applied multiply and independently for each of the transmit/receive antenna pairs.
However, the approaches mentioned above are suboptimal for MIMO-based systems because the physical specifics of the MIMO setup are not used in the estimation process either to reach the best accuracy or to reduce the amount of feedback samples. In addition, the CSI estimation techniques mentioned above are computationally complex. For example, a very effective technique for estimating the time domain tap delay model is based on convex optimization, which incurs high computational complexity, particularly for MIMO-based systems due to the multitude of transmit/receive antenna pairs.